Through-focus scanning optical microscopy applications

Attota, Ravikiran

doi:10.1117/12.2302592

Cited by 4 publications

(2 citation statements)

References 32 publications

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“…Has a larger field of view compared with LSCM, which allows larger samples to be imaged without the need for stitching. Widely used in biological research and can also be used to study materials, such as metals and polymers [237,238].…”

Section: Optical Microscopymentioning

confidence: 99%

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High-Temperature Materials for Complex Components in Ammonia/Hydrogen Gas Turbines: A Critical Review

Alnaeli,

Alnajideen,

Navaratne

et al. 2023

Energies

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This article reviews the critical role of material selection and design in ensuring efficient performance and safe operation of gas turbine engines fuelled by ammonia–hydrogen. As these energy fuels present unique combustion characteristics in turbine combustors, the identification of suitable materials becomes imperative. Detailed material characterisation is indispensable for discerning defects and degradation routes in turbine components, thereby illuminating avenues for improvement. With elevated turbine inlet temperatures, there is an augmented susceptibility to thermal degradation and mechanical shortcomings, especially in the high-pressure turbine blade—a critical life-determining component. This review highlights challenges in turbine design for ammonia–hydrogen fuels, addressing concerns like ammonia corrosion, hydrogen embrittlement, and stress corrosion cracking. To ensure engine safety and efficacy, this article advocates for leveraging advanced analytical techniques in both material development and risk evaluation, emphasising the interplay among technological progress, equipment specifications, operational criteria, and analysis methods.

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Section: Optical Microscopymentioning

confidence: 99%

“…It can be destructive, especially if the sample needs to be stained or sectioned. It has a limited depth of field, which can make it difficult to image samples with a large height or depth [238].…”

Section: Optical Microscopymentioning

confidence: 99%

High-Temperature Materials for Complex Components in Ammonia/Hydrogen Gas Turbines: A Critical Review

Alnaeli,

Alnajideen,

Navaratne

et al. 2023

Energies

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Enhancing 6 nm CD Patterned Defect Classification with TSOM and CNNs

Attota¹,

Anaya

2023

2023 34th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)

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A through‐focus scanning optical microscopy dimensional measurement method based on deep‐learning classification model

Nie

Peng

Jia-jun

2021

Journal of Microscopy

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Through-focus scanning optical microscopy (TSOM) is an economical, noncontact and nondestructive method for rapid measurement of three-dimensional nanostructures. There are two methods using TSOM image to measure the dimensions of one sample, including the library-matching method and the machine-learning regression method. The first has the defects of small measurement range and strict environmental requirements; the other has the disadvantages of feature extraction method greatly influenced by human subjectivity and low measurement accuracy. To solve the problems above, a TSOM dimensional measurement method based on deep-learning classification model is proposed.TSOM images are used to train the ResNet50 and DenseNet121 classification model respectively in this paper, and the test images are used to test the model, the classification result of which is taken as the measurement value. The test results showed that with the number of training linewidths increasing, the mean square error (MSE) of the test images is 21.05 nmš for DenseNet121 model and 31.84 nmš for ResNet50 model, both far lower than machine-learning regression method, and the measurement accuracy is significantly improved. The feasibility of using deep-learning classification model, instead of machine-learning regression model, for dimensional measurement is verified, providing a theoretical basis for further improvement on the accuracy of dimensional measurement.

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Through-focus scanning optical microscopy applications

Cited by 4 publications

References 32 publications

High-Temperature Materials for Complex Components in Ammonia/Hydrogen Gas Turbines: A Critical Review

High-Temperature Materials for Complex Components in Ammonia/Hydrogen Gas Turbines: A Critical Review

Enhancing 6 nm CD Patterned Defect Classification with TSOM and CNNs

A through‐focus scanning optical microscopy dimensional measurement method based on deep‐learning classification model

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